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Dr. Steve Cole's laboratory studies how hormones regulate human and viral genomes. His studies show how stress suppresses immune system function and enhances activity of the HIV and cancer-causing viruses such as Kaposi's Sarcoma Herpes Virus. His laboratory also develops new mathematical tools for analyzing complex gene networks.

Cole's research focuses on the role of cAMP/PKA signaling in regulating global patterns of gene expression. A broad array of viral genomes respond to this cellular signaling pathway, and Cole's lab has mapped several points of interaction between PKA signaling and viral replication cycles. In the case of HIV-1, PKA upregulates the co-receptors CCR5 and CXCR4, induces cellular transcription factors to interact with the viral LTR and suppresses antiviral Type I interferons. In the case of the Kaposi's Sarcoma Herpes Virus (KSHV/HHV-8), PKA upregulates transcription of the key viral transcription factor RTA and post-translationally modifies its trans-activating capacity. Similar mechanisms have been identified for HCMV and HSV-1 and -2. Cole and his colleagues are now evaluating pharmacologic kinase modulators and gene therapeutic manipulation of PKA and downstream transcription factors. These principles have already been applied to developing novel vector-born adjuvants to enhance vaccine-induced cellular immune responses.

In the human genome, PKA mediates hormonal control of ~5,000 genes, but the teleologic principle defining its scope is poorly understood. Cole and associates have combined the mathematics of complex systems with principles from linguistics to identify the biological "meaning" of signal transduction pathways. For example, NF- B "means" inflammation, but the meaning of other signaling pathways is less clear and highly "contextual" (varies with cell type or activity of other signaling pathways). The researchers have developed a series of bioinformatics tools for mapping broad patterns of change in gene expression, inferring the up-stream signaling processes that drive those changes, and identifying combinatorial effects of genes and transcription factors that differ from their separate individual effects. The overarching aim of this work is to elevate genomic analyses out of the crowded field of ~30,000 genes and into a smaller set of abstract principles corresponding to signal transduction pathways and biological response themes.